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  1. 1

    A Comparison Between Levenberg-Marquardt (LM) Intelligent System And Bayesian Regularization (BR) Intelligent System For Flow Regime Classification by Sa'ad, Mohamad Iqbal

    Published 2006
    “…ECT measured the different capacitance value of fluid and produced the data for the classification problem. Multilayed Perceptron (MLP), a type of artificial neural network (ANN) which is widely used in a classification problem is developed using MATLAB 7®. …”
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    Monograph
  2. 2

    Classification System for Heart Disease Using Bayesian Classifier by Magendram, Anusha

    Published 2007
    “…In this system a Bayesian algorithm was used in order to implement the system. …”
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    Thesis
  3. 3

    Feature extraction using active appearance model algorithm with Bayesian classification approach by Nuruzzaman, Mohammad, Hussain, Azham, Mohamad Tahir, Hatim, Abu Seman, Mohamad Amir

    Published 2013
    “…Face recognition is one of the most important and rapidly advanced active research areas of computer science.In spite of the large number of developed algorithms, real-world performance of face recognition has been disappointing. …”
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    Conference or Workshop Item
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    Comparative Analysis Using Bayesian Approach To Neural Network Of Translational Initiation Sites In Alternative Polymorphic Contex by Herman, Nanna Suryana, Husin, Nurul Arneida, Hussin, Burairah

    Published 2012
    “…The objectives of this paper are to develop useful algorithms and to build a new classification model for the case study.The first approach of neural network includes training on algorithms of Resilient Backpropagation,Scaled Conjugate Gradient Backpropagation and Levenberg-Marquardt.The outputs are used in comparison with Bayesian Neural Network for efficiency comparison.The results showed that Resilient Backpropagation have the consistency in all measurement but performs less in accuracy.In second approach,the Bayesian Classifier_01 outperforms the Resilient Backpropagation by successfully increasing the overall prediction accuracy by 16.0%.The Bayesian Classifier_02 is built to improve the accuracy by adding new features of chemical properties as selected by the Information Gain Ratio method,and increasing the length of the window sequence to 201.The result shows that the built model successfully increases the accuracy by 96.0%.In comparison,the Bayesian model outperforms Tikole and Sankararamakrishnan (2008) by increasing the sensitivity by 10% and specificity by 26%. …”
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    Article
  6. 6

    Computational intelligence approach for classification and risk quantification of metabolic syndrome / Habeebah Adamu Kakudi by Habeebah Adamu , Kakudi

    Published 2019
    “…Therefore, the aim of this study is to propose and develop a novel non-clinical technique for the early risk quantification and classification of MetS refered to as genetically optimized Bayesian adaptive resonance theory mapping (GOBAM). …”
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    Thesis
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    Application Of Neural Network In Malaria Parasites Classification by Lim, Chia Li

    Published 2006
    “…Multilayer Perceptron (MLP) network and Radial Basis Function (RBF) network will be developed using MATLAB in which MLP network is trained with Back Propagation, Bayesian Rule and Levenberg-Marquardt learning algorithm and RBF network is trained with k-means clustering algorithm. …”
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    Monograph
  9. 9

    A Voting Technique Of Multilayer Perceptron Ensemble For Classification Application by Talib, Hafizah

    Published 2014
    “…MLPE is produced from singular MLPs that are diverse in term of training algorithm and their initial weights. Three training algorithms used are Levenberg-Marquardt (LM), Resilient Backpropagation (RP) and Bayesian Regularization (BR). …”
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    Thesis
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    A comparative study in classification techniques for unsupervised record linkage model by Ektefa, Mohammadreza, Sidi, Fatimah, Ibrahim, Hamidah, A. Jabar, Marzanah, Memar, Sara

    Published 2011
    “…A variety of record linkage algorithms with different steps have been developed in order to detect such duplicate records. …”
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    Article
  12. 12

    Classification of imbalanced travel mode choice to work data using adjustable svm model by Qian, Y., Aghaabbasi, M., Ali, M., Alqurashi, M., Salah, B., Zainol, R., Moeinaddini, M., Hussein, E.E.

    Published 2021
    “…This study deals with imbalanced mode choice data by developing an algorithm (SVMAK) based on a support vector machine model and the theory of adjusting kernel scaling. …”
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    Article
  13. 13

    An Effective Fast Searching Algorithm for Internet Crawling Usage by Chia, Zhen Hon, Nor Azhar, Ahmad

    Published 2016
    “…The search algorithm is a crucial part in any internet applications. …”
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    Conference or Workshop Item
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    Detection of corneal arcus using rubber sheet and machine learning methods by Ramlee, Ridza Azri

    Published 2019
    “…The benchmark of the classification algorithm for CA is needed to analyze the optimal output of the algorithm. …”
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    Thesis
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    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…The experimental result shows that using Java 2, this method improves the speed of PrefixSpan up to almost two orders of magnitude as well as the memory usage to more than one order of magnitude.…”
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    Conference or Workshop Item
  20. 20

    Modeling of road geometry and traffic accidents by hierarchical object-based and deep learning methods using laser scanning data by Sameen, Maher Ibrahim

    Published 2018
    “…There was a need for efficient segmentation algorithm, optimization strategy, feature extraction and classification, and robust statistical and computational intelligence models to accomplish the set aims. …”
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    Thesis